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Pricing European Options Using Monte Carlo Methods
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Book Synopsis Monte Carlo Methods in Financial Engineering by : Paul Glasserman
Download or read book Monte Carlo Methods in Financial Engineering written by Paul Glasserman and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 603 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the reviews: "Paul Glasserman has written an astonishingly good book that bridges financial engineering and the Monte Carlo method. The book will appeal to graduate students, researchers, and most of all, practicing financial engineers [...] So often, financial engineering texts are very theoretical. This book is not." --Glyn Holton, Contingency Analysis
Book Synopsis Handbook of Monte Carlo Methods by : Dirk P. Kroese
Download or read book Handbook of Monte Carlo Methods written by Dirk P. Kroese and published by John Wiley & Sons. This book was released on 2013-06-06 with total page 627 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and real-world applications More and more of today’s numerical problems found in engineering and finance are solved through Monte Carlo methods. The heightened popularity of these methods and their continuing development makes it important for researchers to have a comprehensive understanding of the Monte Carlo approach. Handbook of Monte Carlo Methods provides the theory, algorithms, and applications that helps provide a thorough understanding of the emerging dynamics of this rapidly-growing field. The authors begin with a discussion of fundamentals such as how to generate random numbers on a computer. Subsequent chapters discuss key Monte Carlo topics and methods, including: Random variable and stochastic process generation Markov chain Monte Carlo, featuring key algorithms such as the Metropolis-Hastings method, the Gibbs sampler, and hit-and-run Discrete-event simulation Techniques for the statistical analysis of simulation data including the delta method, steady-state estimation, and kernel density estimation Variance reduction, including importance sampling, latin hypercube sampling, and conditional Monte Carlo Estimation of derivatives and sensitivity analysis Advanced topics including cross-entropy, rare events, kernel density estimation, quasi Monte Carlo, particle systems, and randomized optimization The presented theoretical concepts are illustrated with worked examples that use MATLAB®, a related Web site houses the MATLAB® code, allowing readers to work hands-on with the material and also features the author's own lecture notes on Monte Carlo methods. Detailed appendices provide background material on probability theory, stochastic processes, and mathematical statistics as well as the key optimization concepts and techniques that are relevant to Monte Carlo simulation. Handbook of Monte Carlo Methods is an excellent reference for applied statisticians and practitioners working in the fields of engineering and finance who use or would like to learn how to use Monte Carlo in their research. It is also a suitable supplement for courses on Monte Carlo methods and computational statistics at the upper-undergraduate and graduate levels.
Book Synopsis Monte Carlo and Quasi-Monte Carlo Methods 1996 by : Harald Niederreiter
Download or read book Monte Carlo and Quasi-Monte Carlo Methods 1996 written by Harald Niederreiter and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monte Carlo methods are numerical methods based on random sampling and quasi-Monte Carlo methods are their deterministic versions. This volume contains the refereed proceedings of the Second International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing which was held at the University of Salzburg (Austria) from July 9--12, 1996. The conference was a forum for recent progress in the theory and the applications of these methods. The topics covered in this volume range from theoretical issues in Monte Carlo and simulation methods, low-discrepancy point sets and sequences, lattice rules, and pseudorandom number generation to applications such as numerical integration, numerical linear algebra, integral equations, binary search, global optimization, computational physics, mathematical finance, and computer graphics. These proceedings will be of interest to graduate students and researchers in Monte Carlo and quasi-Monte Carlo methods, to numerical analysts, and to practitioners of simulation methods.
Book Synopsis Conditional Monte Carlo by : Michael C. Fu
Download or read book Conditional Monte Carlo written by Michael C. Fu and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: Conditional Monte Carlo: Gradient Estimation and Optimization Applications deals with various gradient estimation techniques of perturbation analysis based on the use of conditional expectation. The primary setting is discrete-event stochastic simulation. This book presents applications to queueing and inventory, and to other diverse areas such as financial derivatives, pricing and statistical quality control. To researchers already in the area, this book offers a unified perspective and adequately summarizes the state of the art. To researchers new to the area, this book offers a more systematic and accessible means of understanding the techniques without having to scour through the immense literature and learn a new set of notation with each paper. To practitioners, this book provides a number of diverse application areas that makes the intuition accessible without having to fully commit to understanding all the theoretical niceties. In sum, the objectives of this monograph are two-fold: to bring together many of the interesting developments in perturbation analysis based on conditioning under a more unified framework, and to illustrate the diversity of applications to which these techniques can be applied. Conditional Monte Carlo: Gradient Estimation and Optimization Applications is suitable as a secondary text for graduate level courses on stochastic simulations, and as a reference for researchers and practitioners in industry.
Book Synopsis Pricing American Options Using Monte Carlo Simulation by : Victoria Zhanna Averbukh
Download or read book Pricing American Options Using Monte Carlo Simulation written by Victoria Zhanna Averbukh and published by . This book was released on 1997 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The New Market Wizards by : Jack D. Schwager
Download or read book The New Market Wizards written by Jack D. Schwager and published by John Wiley & Sons. This book was released on 2012-10-10 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for THE NEW MARKET WIZARDS "Jack Schwager simply writes the best books about trading I've ever read. These interviews always give me a lot to think about. If you like learning about traders and trading, you'll find that reading this book is time well spent." -Richard Dennis, President, The Dennis Trading Group, Inc. "Jack Schwager's deep knowledge of the markets and his extensive network of personal contacts throughout the industry have set him apart as the definitive market chronicler of our age." -Ed Seykota "Very interesting indeed!" -John Train, author of The Money Masters "Successful trading demands longtime experience because it requires firsthand knowledge. If there is a shortcut to this requirement, however, it is in reading about the experiences of others. Jack Schwager's book provides that shortcut. If you find yourself sweating upon occasion as you read, then you're as close to the trading experience as you can get without actually doing it yourself." -Robert R. Prechter, Jr., editor, The Elliott Wave Theorist THE NEW MARKET WIZARDS Some traders distinguish themselves from the herd. These supertraders make millions of dollars-sometimes in hours-and consistently outperform their peers. As he did in his acclaimed national bestseller, Market Wizards, Jack Schwager interviews a host of these supertraders, spectacular winners whose success occurs across a spectrum of financial markets. These traders use different methods, but they all share an edge. How do they do it? What separates them from the others? What can they teach the average trader or investor? In The New Market Wizards, these wildly successful traders relate the financial strategies that have rocketed them to success, as well as the embarrassing losses that have proven them all too human. Meet the Wizards of Wall Street: * Stan Druckenmiller, who, as manager of the Soros Quantum Fund, realized an average annual return of more than 38 percent on assets ranging between $2.0 and $3.5 billion * William Eckhardt, a mathematician who, in collaboration with trader Richard Dennis, selected and trained the now-legendary circle known as the Turtles * Bill Lipschutz, a former architect who, for eight years, was Salomon Brothers' largest and most successful currency trader * Blair Hull, a one-time blackjack player who began an options trading company with Asking the questions that readers with an interest in the financial markets would love to pose to the financial superstars, and filled with candid appraisals, The New Market Wizards takes its place as a classic.
Book Synopsis PDE and Martingale Methods in Option Pricing by : Andrea Pascucci
Download or read book PDE and Martingale Methods in Option Pricing written by Andrea Pascucci and published by Springer Science & Business Media. This book was released on 2011-04-15 with total page 727 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an introduction to the mathematical, probabilistic and numerical methods used in the modern theory of option pricing. The text is designed for readers with a basic mathematical background. The first part contains a presentation of the arbitrage theory in discrete time. In the second part, the theories of stochastic calculus and parabolic PDEs are developed in detail and the classical arbitrage theory is analyzed in a Markovian setting by means of of PDEs techniques. After the martingale representation theorems and the Girsanov theory have been presented, arbitrage pricing is revisited in the martingale theory optics. General tools from PDE and martingale theories are also used in the analysis of volatility modeling. The book also contains an Introduction to Lévy processes and Malliavin calculus. The last part is devoted to the description of the numerical methods used in option pricing: Monte Carlo, binomial trees, finite differences and Fourier transform.
Book Synopsis Monte Carlo and Quasi-Monte Carlo Methods by : Ronald Cools
Download or read book Monte Carlo and Quasi-Monte Carlo Methods written by Ronald Cools and published by Springer. This book was released on 2016-06-13 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the refereed proceedings of the Eleventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Leuven (Belgium) in April 2014. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in finance, statistics and computer graphics.
Book Synopsis Mathematical Modeling and Methods of Option Pricing by : Lishang Jiang
Download or read book Mathematical Modeling and Methods of Option Pricing written by Lishang Jiang and published by World Scientific. This book was released on 2005 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the perspective of partial differential equations (PDE), this book introduces the Black-Scholes-Merton's option pricing theory. A unified approach is used to model various types of option pricing as PDE problems, to derive pricing formulas as their solutions, and to design efficient algorithms from the numerical calculation of PDEs.
Book Synopsis The Complete Guide to Option Pricing Formulas by : Espen Gaarder Haug
Download or read book The Complete Guide to Option Pricing Formulas written by Espen Gaarder Haug and published by Professional Finance & Investment. This book was released on 2007-01-08 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accompanying CD-ROM contains ... "all pricing formulas, with VBA code and ready-to-use Excel spreadsheets and 3D charts for Greeks (or Option Sensitivities)."--Jacket.
Book Synopsis An Introduction to Financial Option Valuation by : Desmond J. Higham
Download or read book An Introduction to Financial Option Valuation written by Desmond J. Higham and published by Cambridge University Press. This book was released on 2004-04-15 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a lively textbook providing a solid introduction to financial option valuation for undergraduate students armed with a working knowledge of a first year calculus. Written in a series of short chapters, its self-contained treatment gives equal weight to applied mathematics, stochastics and computational algorithms. No prior background in probability, statistics or numerical analysis is required. Detailed derivations of both the basic asset price model and the Black–Scholes equation are provided along with a presentation of appropriate computational techniques including binomial, finite differences and in particular, variance reduction techniques for the Monte Carlo method. Each chapter comes complete with accompanying stand-alone MATLAB code listing to illustrate a key idea. Furthermore, the author has made heavy use of figures and examples, and has included computations based on real stock market data.
Book Synopsis Monte Carlo Methods in Finance by : William Johnson
Download or read book Monte Carlo Methods in Finance written by William Johnson and published by HiTeX Press. This book was released on 2024-10-16 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Monte Carlo Methods in Finance: Simulation Techniques for Market Modeling" presents a sophisticated and in-depth exploration of Monte Carlo simulations, a vital tool in modern financial analysis. This book deftly bridges the gap between theoretical constructs and practical implementation, guiding readers through a comprehensive understanding of how these methods unlock insights into the complexities of financial markets. Through capturing the randomness and volatility inherent in financial systems, Monte Carlo techniques provide a structured approach to modeling uncertainty, pricing derivatives, optimizing portfolios, and managing risk with precision and rigor. With a focus on making advanced concepts accessible, this book seamlessly integrates foundational theories with real-world applications. Each chapter meticulously explores critical subjects—ranging from stochastic processes and option pricing to credit risk and machine learning—while providing clear step-by-step Python implementations. As readers progress, they gain robust skills in executing simulations and interpreting results, empowering them to make informed financial decisions. Whether you are a student, a practitioner, or someone with a keen interest in quantitative finance, this text serves as an invaluable resource for mastering the intricacies of Monte Carlo methods and their impactful role in shaping contemporary finance.
Book Synopsis Monte Carlo Methods and Models in Finance and Insurance by : Ralf Korn
Download or read book Monte Carlo Methods and Models in Finance and Insurance written by Ralf Korn and published by CRC Press. This book was released on 2010-02-26 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Rom
Download or read book GPU Gems 2 written by Matt Pharr and published by Addison-Wesley Professional. This book was released on 2005 with total page 814 pages. Available in PDF, EPUB and Kindle. Book excerpt: More useful techniques, tips, and tricks for harnessing the power of the new generation of powerful GPUs.
Book Synopsis Algebraic Structures and Applications by : Sergei Silvestrov
Download or read book Algebraic Structures and Applications written by Sergei Silvestrov and published by Springer Nature. This book was released on 2020-06-18 with total page 976 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the latest advances in algebraic structures and applications, and focuses on mathematical concepts, methods, structures, problems, algorithms and computational methods important in the natural sciences, engineering and modern technologies. In particular, it features mathematical methods and models of non-commutative and non-associative algebras, hom-algebra structures, generalizations of differential calculus, quantum deformations of algebras, Lie algebras and their generalizations, semi-groups and groups, constructive algebra, matrix analysis and its interplay with topology, knot theory, dynamical systems, functional analysis, stochastic processes, perturbation analysis of Markov chains, and applications in network analysis, financial mathematics and engineering mathematics. The book addresses both theory and applications, which are illustrated with a wealth of ideas, proofs and examples to help readers understand the material and develop new mathematical methods and concepts of their own. The high-quality chapters share a wealth of new methods and results, review cutting-edge research and discuss open problems and directions for future research. Taken together, they offer a source of inspiration for a broad range of researchers and research students whose work involves algebraic structures and their applications, probability theory and mathematical statistics, applied mathematics, engineering mathematics and related areas.
Book Synopsis Monte Carlo Simulation and Finance by : Don L. McLeish
Download or read book Monte Carlo Simulation and Finance written by Don L. McLeish and published by John Wiley & Sons. This book was released on 2011-09-13 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monte Carlo methods have been used for decades in physics, engineering, statistics, and other fields. Monte Carlo Simulation and Finance explains the nuts and bolts of this essential technique used to value derivatives and other securities. Author and educator Don McLeish examines this fundamental process, and discusses important issues, including specialized problems in finance that Monte Carlo and Quasi-Monte Carlo methods can help solve and the different ways Monte Carlo methods can be improved upon. This state-of-the-art book on Monte Carlo simulation methods is ideal for finance professionals and students. Order your copy today.
Book Synopsis Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk by : Fahed Mostafa
Download or read book Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk written by Fahed Mostafa and published by Springer. This book was released on 2017-02-28 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book demonstrates the power of neural networks in learning complex behavior from the underlying financial time series data. The results presented also show how neural networks can successfully be applied to volatility modeling, option pricing, and value-at-risk modeling. These features mean that they can be applied to market-risk problems to overcome classic problems associated with statistical models.